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🎁Tekan Play Demo untuk lihat bagaimana Customer Loyalty Agent mengurus program kesetiaan.
Demo Complete — All Stages Generated
01 WhatsApp Command
02 Loyalty Dashboard
Menunggu Sedang aktif Selesai
03 Python Script Generation
1
📥
Ambil data pelangganCRM — points, spend, tier, history
2
🧮
Kira tier & pointsPurchase → points conversion + auto-upgrade
3
🎁
Cadangkan rewardPadankan reward mengikut tier & spend
4
📊
Laporan & analisisEngagement trends + redemption history
import requests, json, pandas as pd
CRM_API = "https://api.retail.com/v2/loyalty"
def fetch_customers():
resp = requests.get(CRM_API + "/customers")
return resp.json().get("customers", [])
def calculate_tier(points):
if points >= 5000: return "Platinum"
if points >= 2000: return "Gold"
if points >= 500: return "Silver"
return "Bronze"
def suggest_reward(customer):
if customer["tier"] == "Platinum": return "VIP access"
if customer["tier"] == "Gold": return "RM 50 reward"
if customer["tier"] == "Silver": return "20% voucher"
return "Welcome bonus"
def analyze_loyalty(customers):
for c in customers:
c["tier"] = calculate_tier(c["points"])
c["reward"] = suggest_reward(c)
return customers
report = analyze_loyalty(fetch_customers())
print(json.dumps(report, indent=2))
04 Block Diagram
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05 System Schematic
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⚠️ Protect customer data and points balance per PDPA requirements.
06 Simulasi Loyalty Points
Mula Analisis
Ahmad B.2,450GoldRM 50 reward
Siti K.5,800PlatinumVIP access
Rajesh M.890Silver20% voucher
Linda T.120BronzeWelcome bonus
Summary9,2604 tiers4 rewards
Terminal Log
[SISTEM] Retail Customer Loyalty Agent sedia
System Architecture
🤖 Agent Layer
Customer fetcher
Points calc
Tier engine
Reward suggester
🛒 Retail Layer
CRM API
Points ledger
Redemption log
Engagement analytics
Safety Notes
- ⚠️ Protect customer data and points balance per PDPA requirements.
- Human review required before bulk reward disbursement.
- Configure role-based access for loyalty dashboards.
- Browser demo does not touch real CRM APIs.